Winning Back Lost Customers

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For any service company that bills on a recurring basis, a key variable is the rate of churn: How many customers cancel? In many competitive industries, churn can be substantial—some wireless carriers, for instance, lose 3% of subscribers each month. (Other businesses plagued by churn include insurance companies, gyms, and online streaming services.) Companies with high churn typically spend vast sums on marketing to try to replace all those defectors. New research shows that they might be better served by smart strategies aimed at getting lost customers to come back to the fold.

V. Kumar, a marketing professor at Georgia State University who studies “win back” strategies, cites three reasons companies should focus more energy on lapsed customers. First, these people have demonstrated a need for the service, making them far better prospects than random names on a cold-call list. Second, they are familiar with the company, eliminating the need to create brand awareness and educate them about the offering and thus reducing the cost of marketing to them. Third and most important, recent technology, particularly more-sophisticated customer databases, allows companies to draw on information about how people used their service the first time around to craft more-successful win-back offers and to identify and go after the most profitable defectors.

Pitching the Right Offer

A telecom firm tested four win-back offers with 40,000 customers, looking not only at which offer lured back the most people but also at which was the most profitable.

Kumar and two colleagues studied data on more than 53,000 customers who left a telecom company over a seven-year period. To help focus the firm’s ongoing efforts to win such people back, they examined how each lost customer behaved before canceling, why each canceled (many companies ask departing customers this question), how each responded to various win-back offers, and how profitable each one who signed on again subsequently became. As they parsed the data, they sought to answer four questions.

How likely is a given customer to come back?

Many companies try to regain every lost customer, but this can sap marketing dollars; firms will be more efficient if they focus on people whose prior behavior suggests a predisposition to return. The researchers found that customers who have referred others, who have never complained, or who have had complaints that were satisfactorily resolved are the best bets. Reasons for leaving are also predictive: Customers who canceled because of price are more likely to come back than those who left because of poor service, and people who cited both reasons for quitting are the least likely of all to return.

Kumar visited telecom companies around the world to explore their win-back strategies and found that many are experimenting with “propensity models” like this one. But few are investigating which customers would be most valuable to win back—the issue addressed by the following questions.

How have your win-back strategies changed?There’s more sophistication in the analytics we’re doing around individual customers and what their experience was with us the first time around. We can now do personalized marketing at scale—customizing the message, the offer, the pricing. And we have new services, such as one-gigabit internet speeds and home automation and security systems, that give lost customers a reason to take a second look. People are more likely to come back if we improve the value proposition. Win-back is definitely becoming more important—and we’re getting better at it.

How do you decide what to offer lost customers?By understanding why a particular household left us, we can pick up the thread and respond. This doesn’t just help with win-back—we also have a pretty sophisticated retention program, and as we capture information about why customers intend to leave, we use real-time decision engines to inform the conversation and try to keep them with us. There’s an art and a science to this—it’s not just math. It requires inventiveness and creative flair.

Has this work changed how you deal with customers who haven’t left?Yes. The analytics that guide our win-back efforts have helped us better understand the customer experience. For instance, we’re more mindful of certain trigger points in a customer’s first life with us—such as the time when someone rolls off an introductory discount. We pay very close attention during those moments, because we’re aware of the economics of retaining customers versus having to win them back.

How long will a reacquired customer stay, and how much will he or she spend?

There’s little point in wooing back someone who will depart again a few months later, so it’s useful to predict how long a returnee will stay on board. The researchers expected that consumers who bolted once would depart quickly during their second stint. In fact they generally stayed longer, and customers who defected because of price—behavior suggestive of fickle deal seekers—stayed the longest of all. Second-time customers in the study had an average lifetime value of $1,410, versus just $1,262 during their initial run with the service—highlighting an important upside of win-back strategies.

Which people should get which offers?

Many firms have one-size-fits-all incentives. The telecom firm targeted 40,000 lapsed customers whose prior behavior indicated they were likely to return and, with help from the researchers, tested four inducements on them. One group was offered a discount. One could get a service upgrade, such as a free premium cable channel. One could get a discount and an upgrade. And members of one received offers tailored to their reasons for leaving—a customer who defected because of price was offered a discount, while someone who canceled because of poor service was offered an upgrade. The bundled offer yielded the highest win-back rate (47%), followed by the tailored offer and the stand-alone discount offer (both 45%). The stand-alone upgrade offer yielded a 41% win-back rate.

Which win-back strategy is the most profitable?

Knowing what kinds of offers lure back the most customers isn’t enough; the costs and returns of each are important too. Although a service upgrade has the lowest success rate, it’s the cheapest strategy and has the highest return on investment. And while the bundled offer has the highest success rate, it also has the highest cost and the lowest ROI. Kumar notes that companies don’t always choose the strategy that will maximize profit, because many are in industries where market share is paramount. For most companies with subscription models, he says, “Wall Street rewards the acquisition rate—how many customers did you add this quarter?—rather than how much money you made from those customers.” Kumar sees this as shortsighted, but it explains why firms might utilize the strategy most likely to attract the largest number of returning customers, even at the expense of profit.

Many companies have a lot to learn about bringing back lost customers. Simply identifying those who are the most likely to sign up again, rather than appealing to every defector, can increase win-back rates eightfold. And a large company with multiple product lines, such as a telecom providing landline, cable, wireless, and home security services, can benefit from more-sophisticated ways of analyzing customer behavior to offer enticing bundles. “Too many companies go after whoever they’ve lost, throwing all these offers at them, hoping something will work,” Kumar says. “I hope this study helps change the way they operate.”